Oumer Abdu, Abraham Mihret, Nuri Aliya
Department of Public Health, College of Medicine and Health Sciences, Dire Dawa University, Dire Dawa, Ethiopia.
Front Nutr. 2022 Apr 25;9:855149. doi: 10.3389/fnut.2022.855149. eCollection 2022.
Dietary pattern analysis is a robust statistical procedure that efficiently characterize the dietary intakes of individuals. However, there is a lack of robust dietary intake evidence beyond nutrient intake in Ethiopia. This study was to answer, what are the major dietary consumption patterns and its predictors among pregnant women in Ethiopia.
A facility-based survey among 380 randomly selected pregnant women using a contextualized food frequency questionnaire (FFQ) over 1 month recall was used. The frequency of food consumption was standardized to daily frequency equivalents, and a sequential exploratory factor analysis was used to derive major dietary patterns. A multivariable ordinary logistic regression model was fitted with all its assumptions.
Three major dietary patterns ("fruits and animal-source foods," "cereals, tubers, and sweet foods," "legumes and vegetables"), explaining 65% of the total variation were identified. Women snacks (AOR = 1.93; 1.23-2.75), without food aversion (AOR = 1.59; 1.08-2.35), non-fasting (AOR = 0.75; 1.12-2.12), and receiving nutritional counseling (AOR = 1.96; 1.25-3.07) were significantly positively associated with a higher tercile of fruits and animal-source food consumption. Non-working mothers (AOR = 1.8;1.23-2.76), chronic disease (AOR = 1.88; 1.14-3.09), or received nutritional counseling (AOR = 1.33; 0.88-2.01), were fasting (AOR = 1.33;0.88-2.01), and no food cravings (AOR = 4.27;2.67-6.84), and aversion (AOR = 1.60;1.04-2.44) had significantly higher odds of consuming cereals, tubers, and sweet foods. Literacy (AOR = 1.87; 1.14-3.09), urban residence (AOR = 2.10; 1.10-3.93), low socioeconomic class (AOR = 2.68; 1.30-5.23), and skipping meals (AOR = 1.73; 1.15-2.62) were associated with higher odds of legume and vegetable consumption.
Socioeconomic class, literacy, occupation, getting nutritional counseling, habits of food craving, food aversion, and fasting can predict a woman's dietary pattern.
饮食模式分析是一种强大的统计方法，能够有效地描述个体的饮食摄入情况。然而，埃塞俄比亚缺乏除营养素摄入之外的可靠饮食摄入证据。本研究旨在回答埃塞俄比亚孕妇的主要饮食消费模式及其预测因素是什么。
采用基于机构的调查，对380名随机选择的孕妇使用经过情境化的食物频率问卷（FFQ），回顾1个月的饮食情况。食物消费频率被标准化为每日频率当量，并采用序列探索性因子分析来推导主要饮食模式。拟合了一个满足所有假设的多变量普通逻辑回归模型。
确定了三种主要饮食模式（“水果和动物源性食物”、“谷物、块茎和甜食”、“豆类和蔬菜”），解释了总变异的65%。吃零食的女性（调整后比值比[AOR]=1.93；1.23 - 2.75）、没有食物厌恶的女性（AOR = 1.59；1.08 - 2.35）、不禁食的女性（AOR = 0.75；1.12 - 2.12）以及接受营养咨询的女性（AOR = 1.96；1.25 - 3.07）与水果和动物源性食物消费处于较高三分位数显著正相关。无工作的母亲（AOR = 1.8；1.23 - 2.76）、患有慢性病的母亲（AOR = 1.88；1.14 - 3.09）、接受营养咨询的母亲（AOR = 1.33；0.88 - 2.01）、禁食的母亲（AOR = 1.33；0.88 - 2.01）、没有食物渴望的母亲（AOR = 4.27；2.67 - 6.84）以及有食物厌恶的母亲（AOR = 1.60；1.04 - 2.44）食用谷物、块茎和甜食的几率显著更高。识字（AOR = 1.87；1.14 - 3.09）、居住在城市（AOR = 2.10；1.10 - 3.93）、社会经济地位低（AOR = 2.68；1.30 - 5.23）以及不规律进餐（AOR = 1.73；1.15 - 2.62）与豆类和蔬菜消费几率较高相关。
社会经济地位、识字程度、职业、接受营养咨询、食物渴望习惯、食物厌恶和禁食可以预测女性的饮食模式。
